open_iA

University of Applied Sciences Upper Austria

Wels | Website

Other research infrastructure

Short Description

open_iA is a modular open source software tool for the visual analysis and processing of volumetric datasets, with a focus on industrial CT datasets.

As graphical user interface the cross-plattform framework Qt is used, which facilitates an easy to use and attractive interface. In-house visualisation and image processing algorithms are supported by algorithms of the ITK and VTK toolkit, which make open_iA a powerful tool for both 3D visualisation and CT data analysis. open_iA is capable of loading various volume dataset formats as well as different surface model formats. It provides slice by slice navigation in its 2D views, common 3D navigation with arbitrary cutting planes in the 3D view, together with custom views for individual visualization. open_iA provides command line access as well as interfaces to various libraries in terms of image processing, segmentation, registration, feature extraction, visualization, immersive analytics as well as machine learning. open_iA is easily extensible and serves as central development platform of the research group computed tomography and therefore integrates all algorithms and methods developed within the group.

Links:
https://github.com/3dct/open_iA
https://www.3dct.at/cms2/index.php/de/software/open-ia
https://www.youtube.com/c/iAnalyseCTDev

Citation:
Bernhard Fröhler, Johannes Weissenböck, Marcel Schiwarth, Johann Kastner, and Christoph Heinzl, open_iA: A tool for processing and visual analysis of industrial computed tomography datasets, Journal of Open Source Software, 4 (35), 2019, 1185, doi: 10.21105/joss.01185.

Contact Person

FH-Assistenzprof. DI (FH) Dr. Christoph Heinzl

Research Services

Application and development of algorithms, technologies and methods for visual analysis (with a focus on X-ray computed tomography) using complex data from a wide variety of domains.

Methods & Expertise for Research Infrastructure

Tailored filters, analysis modules and visualization techniques for the visual analysis of complex industrial X-ray computed tomography data

FH-Assistenzprof. DI (FH) Dr. Christoph Heinzl
Fakultät für Technik und Angewandte Naturwissenschaften
+43 50804 44406
christoph.heinzl@fh-wels.at
https://pure.fh-ooe.at/de/persons/christoph-heinzl
GNU General Public License v3.0
EU H2020‑MSCA‑ITN‑2020 xCTing: Enabling X‑Ray CT Based Industry 4.0 Process Chains by Training Next Generation Research Experts (2021 ‑ 2025), 9 Partners, 6 Associated partners, 7 Countries, https://xcting-itn.eu/

Land OÖ FTI X‑Pro: Erforschung und Entwicklung benutzer‑zentrierter Methoden für Cross‑Virtuality Analytics von Produktionsdaten (2020 ‑ 2024), 1 Partners, 1 Country, https://x-pro.fh-ooe.at/

Dissertationsprogramm der FHOÖ 2020, AugmeNDT ‑ Immersive On‑Site and Remote Analysis of Complex Composite Materials using Augmented Reality Techniques (2020 ‑ 2023), 4 Partners, 2 Countries

Dissertationsprogramm der FHOÖ 2020, COMPARE ‑ Comparative Analysis of Temporal Trends in Multidimensional Data Ensembles from Materials Testing (2020 ‑ 2023), 4 Partners, 2 Countries

FFG Takeoff BeyondInspection: Digitalisierungsplattform zur prädiktiven Bewertung von Luftfahrtbauteilen mittels multimodaler multiskalarer Inspektion (2019 ‑ 2022), 4 Partners, 1 Country, http://www.3dct.at/beyondinspection
A. Gall, E. Gröller, C. Heinzl, ImNDT: Immersive Workspace for the Analysis of Multidimensional Material
Data From Non‑Destructive Testing, In ACM Symposium on Virtual Reality Software and Technology (VRST)
2021, Osaka / Japan, 2021, pp. 11, doi:10.1145/3489849.3489851

A. Heim, E. Gröller, C. Heinzl, CoSi: Visual Comparison of Similarities in High‑Dimensional Data Ensembles,
In Vision, Modeling, and Visualization (2021), VMV 2021, Dresden / Germany, 2021, pp. 8, doi:10.2312/vmv.20211378

B. Fröhler, T. Elberfeld, T. Möller, H.-C. Hege, J. Weissenböck, J. De Beenhouwer, J. Sijbers, J. Kastner, C. Heinzl, A Visual Tool for the Analysis of Algorithms for Tomographic Fiber Reconstruction in Materials Science, Computer Graphics Forum, 38 (3), 2019, pp. 273–283, doi: 10.1111/cgf.13688.

J. Weissenböck, B. Fröhler, E. Gröller, J. Kastner, C. Heinzl, Dynamic Volume Lines: Visual Comparison of 3D Volumes through Space-filling Curves, Transactions on Visualization and Computer Graphics, 25 (1), 2018, pp. 1040–1049, doi: 10.1109/TVCG.2018.2864510.

A. Amirkhanov, A. Amirkhanov, D. Salaberger, J. Kastner, E. Gröller, C. Heinzl, Visual Analysis of Defects in Glass Fiber Reinforced Polymers for 4DCT Interrupted In situ Tests, Computer Graphics Forum, 35 (3), 2016, pp. 201–210, doi: 10.1111/cgf.12896.

B. Fröhler, T. Möller, and C. Heinzl, GEMSe: Visualization-Guided Exploration of Multi-channel Segmentation Algorithms, Computer Graphics Forum, 35 (3), 2016, pp. 191–200, doi: 10.1111/cgf.12895.

J. Weissenböck, A. Amirkhanov, W. Li, A. Reh, A. Amirkhanov, E. Gröller, Johann Kastner, C. Heinzl, FiberScout: An Interactive Tool for Exploring and Analyzing Fiber Reinforced Polymers, IEEE Pacific Visualization Symposium, Yokohama, 2014, pp. 153–160, doi: 10.1109/PacificVis.2014.52.

A. Amirkhanov, B. Fröhler, J. Kastner, E. Gröller, C. Heinzl, InSpectr: Multi-Modal Exploration, Visualization, and Analysis of Spectral Data, Computer Graphics Forum, 33 (3), 2014, pp. 91–100, doi: 10.1111/cgf.12365.